This invention relates to a system for triage of audio recordings for processing by a speech analytics system.
Speech analytics systems extract information about speech content present in audio data. Some exemplary types of information include topical information, locations and percentages of speech vs. non-speech data, an emotional character of the speech, and so on.
Speech analytics systems are conventionally implemented as software running on general purpose computers. Due to limitations of the current state of the art in general purpose computing, such computers have a limited processing capacity. Given large amounts of audio data (e.g., a large number of audio recordings), a general purpose computer may be unable to process all of the audio data within an acceptable period of time. For this reason, conventional speech analytics systems may choose a sampling (e.g., a random sampling) of the audio data for analysis. The amount of audio data in the sampling is chosen such that it matches or is less than the processing capacity of the general purpose computer.
While such a sampling effectively reduces the amount of data processed by the computer to a manageable level, it does not take into account the quality of the audio data in the sample. For example, in a large number of audio recordings, some recordings may have characteristics which allow for extraction of more information (i.e., provide higher recall) when processed by the speech analytics system than others. Randomly sampling the large number of audio recordings may result in a number of low recall recordings being included in the sample while a number of high recall recordings are excluded from the sample. Including low recall recordings in the sample while excluding high recall recordings can result in a sub-optimal performance of the speech analytics system.